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02_​Performing_​a_​k-Medoids_​Clustering

Performing a k-Medoids clustering

This workflow shows how to perform a clustering of the iris dataset using the k-Medoids node.

Performing a k-Medoids Clustering This workflow shows how to cluster the iris datasetwith the k-Medoids node. Visualization Perform clustering using a Distance Matrix Perform clustering using a Distance Measure Visualization assign colorsto classesassign shapeto clusterscreate scatterplotload datasearch for three clusterscreate distancemeasurecalculate distancematrixsearch for three clusterscreate scatterplotassign shapeto clustersassign colorsto classes Color Manager Shape Manager Scatter Plot(local) Table Reader k-Medoids Numeric Distances Distance MatrixCalculate k-Medoids Scatter Plot(local) Shape Manager Color Manager Performing a k-Medoids Clustering This workflow shows how to cluster the iris datasetwith the k-Medoids node. Visualization Perform clustering using a Distance Matrix Perform clustering using a Distance Measure Visualization assign colorsto classesassign shapeto clusterscreate scatterplotload datasearch for three clusterscreate distancemeasurecalculate distancematrixsearch for three clusterscreate scatterplotassign shapeto clustersassign colorsto classes Color Manager Shape Manager Scatter Plot(local) Table Reader k-Medoids Numeric Distances Distance MatrixCalculate k-Medoids Scatter Plot(local) Shape Manager Color Manager

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: Adrian Nembach
Created at: 2016-05-19
On NodePit since: 2025-04-02
Last update: 2026-01-07
Created with KNIME version: v4.1.0
Tags: clustering k-Medoids machine learning data mining

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